Evidence map›Paper›PMID 38868917›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Metal-Organic Frameworks in Surface Enhanced Raman Spectroscopy-Based Analysis of Volatile Organic Compounds.

Juan A Allegretto, Jakub Dostalek

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Juan A AllegrettoLaboratory for Life Sciences and Technology (LiST), Department of Medicine, Faculty of Medicine and Dentistry, Danube Private University, Krems, 3500, Austria.ORCID https://orcid.org/0000-0002-7371-2610
Jakub DostalekLaboratory for Life Sciences and Technology (LiST), Department of Medicine, Faculty of Medicine and Dentistry, Danube Private University, Krems, 3500, Austria.ORCID https://orcid.org/0000-0002-0431-2170

Funding

Austrian Science Fund 10.55776/ESP93Czech Ministry of Education SENDISO -CZ.02.01.01/00/22_008/0004596
6 · The paper itself

Abstract

Volatile Organic Compounds (VOC) are a major class of environmental pollutants hazardous to human health, but also highly relevant in other fields including early disease diagnostics and organoleptic perception of aliments. Therefore, accurate analysis of VOC is essential, and a need for new analytical methods is witnessed for rapid on-site detection without complex sample preparation. Surface-Enhanced Raman Spectroscopy (SERS) offers a rapidly developing versatile analytical platform for the portable detection of chemical species. Nonetheless, the need for efficient docking of target analytes at the metallic surface significantly narrows the applicability of SERS. This limitation can be circumvented by interfacing the sensor surface with Metal-Organic Frameworks (MOF). These materials featuring chemical and structural versatility can efficiently pre-concentrate low molecular weight species such as VOC through their ordered porous structure. This review presents recent trends in the development of MOF-based SERS substrates with a focus on elucidating respective design rules for maximizing analytical performance. An overview of the status of the detection of harmful VOC is discussed in the context of industrial and environmental monitoring. In addition, a survey of the analysis of VOC biomarkers for medical diagnosis and emerging applications in aroma and flavor profiling is included.

Indexed as

MOFRamansensingSERSvolatile organic compounds

Identifiers

PMID38868917
PMCPMC11321619

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.